Pinned Repositories
Big-Basket-Chatbot
Brain-Tumor-Detection-with-CNN-based-model
Chicken-Disease-Classification
CIFAR-10-classification-by-AlexNet-in-PyTorch
This code contains the implementation on AlexNet in PyTorch from scratch. It has been trained to classified CIFAR-10 dataset.
coursera-deep-learning-specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks;
Disaster-and-Tweets
DL-based-Collaborative-Filtering-Model-with-Content-based-Support
A book recommendation system that harnesses the power of Deeplearning based Collaborative Filtering complemented by content-based filtering to tackle the cold-start problem. Additionally, this model has the capability to recommend books based on external text queries, enhancing the versatility of the recommendations.
End-to-end-CNN-and-Hybrid-CNN-RF-Brain-Tumor-Detection
This project employs TensorFlow to develop a CNN-based brain tumor detection system. Moreover, a hybrid model, combining a pre-trained CNN as a feature extractor with a LightGBM Classifier, achieved even better performance, underscoring the efficacy of hybrid approaches in medical image analysis.
Inception-Based-Fashion-MNIST-Classification-in-PyTorch
This project showcases the creation of a custom inception block using PyTorch and its application to classify the MNIST Fashion dataset. The integration of F1 score and a confusion matrix enhances the evaluation process.
Lifestyle-Prediction-using-Ensemble-Learning
Designed an ensemble of diverse classifiers delivering an F1 score of 87.63% in predicting healthy vs. unhealthy lifestyles from tabular data
anindya2306's Repositories
anindya2306/Big-Basket-Chatbot
anindya2306/Brain-Tumor-Detection-with-CNN-based-model
anindya2306/Chicken-Disease-Classification
anindya2306/CIFAR-10-classification-by-AlexNet-in-PyTorch
This code contains the implementation on AlexNet in PyTorch from scratch. It has been trained to classified CIFAR-10 dataset.
anindya2306/coursera-deep-learning-specialization
Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks;
anindya2306/Disaster-and-Tweets
anindya2306/DL-based-Collaborative-Filtering-Model-with-Content-based-Support
A book recommendation system that harnesses the power of Deeplearning based Collaborative Filtering complemented by content-based filtering to tackle the cold-start problem. Additionally, this model has the capability to recommend books based on external text queries, enhancing the versatility of the recommendations.
anindya2306/End-to-end-CNN-and-Hybrid-CNN-RF-Brain-Tumor-Detection
This project employs TensorFlow to develop a CNN-based brain tumor detection system. Moreover, a hybrid model, combining a pre-trained CNN as a feature extractor with a LightGBM Classifier, achieved even better performance, underscoring the efficacy of hybrid approaches in medical image analysis.
anindya2306/Inception-Based-Fashion-MNIST-Classification-in-PyTorch
This project showcases the creation of a custom inception block using PyTorch and its application to classify the MNIST Fashion dataset. The integration of F1 score and a confusion matrix enhances the evaluation process.
anindya2306/Lifestyle-Prediction-using-Ensemble-Learning
Designed an ensemble of diverse classifiers delivering an F1 score of 87.63% in predicting healthy vs. unhealthy lifestyles from tabular data
anindya2306/Neural_Style_Transfer
anindya2306/Noisy-and-Low-Light-Image-Enhancement-with-CNN
The goal of the project is to develop a computer vision system that can enhance low light and noisy images. Specifically, given an input image containing a region of interest (ROI) that is dark and/or noisy, the system should be able to produce an enhanced image of that ROI that is visually pleasing and improves the overall image quality.
anindya2306/py
Repository to store sample python programs for python learning
anindya2306/segmenter
[ICCV2021] Official PyTorch implementation of Segmenter: Transformer for Semantic Segmentation
anindya2306/Sleep-Stage-Classification-From-EEG-ML-vs-DL
Implemented machine learning models (LGBM, CNN-LSTM) for sleep stage prediction from raw EEG signals, contributing to efficient diagnosis of sleep disorders.
anindya2306/Summerize-Text